Extending Monolingual Semantic Textual Similarity Task to Multiple Cross-lingual Settings

2016-05-01 · LREC 2016 5 · Yoshihiko Hayashi, Wentao Luo

This paper describes our independent effort for extending the monolingual semantic textual similarity (STS) task setting to multiple cross-lingual settings involving English, Japanese, and Chinese. So far, we have adopted a {``}monolingual similarity after translation{''} strategy to predict the semantic similarity between a pair of sentences in different languages. With this strategy, a monolingual similarity method is applied after having (one of) the target sentences translated into a pivot language. Therefore, this paper specifically details the required and developed resources to implement this framework, while presenting our current results for English-Japanese-Chinese cross-lingual STS tasks that may exemplify the validity of the framework.

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Tasks

SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation

2016-06-01 · SEMEVAL 2016 6 · Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab 외

Machine Translation Natural Language Inference Question Answering Semantic Textual Similarity

WOLVESAAR at SemEval-2016 Task 1: Replicating the Success of Monolingual Word Alignment and Neural Embeddings for Semantic Textual Similarity

2016-06-01 · SEMEVAL 2016 6 · Hannah Bechara, Rohit Gupta, Liling Tan, Constantin Or{\u{a}}san 외

Information Retrieval Machine Translation Semantic Textual Similarity Text Summarization+2

FCICU at SemEval-2017 Task 1: Sense-Based Language Independent Semantic Textual Similarity Approach

2017-08-01 · SEMEVAL 2017 8 · Basma Hassan, Samir AbdelRahman, Reem Bahgat, Ibrahim Farag

This paper describes FCICU team systems that participated in SemEval-2017 Semantic Textual Similarity task (Task1) for monolingual and cross-lingual sentence pairs. A sense-based language independent textual similarity a…

Machine Translation Semantic Textual Similarity Sentence

ITNLP-AiKF at SemEval-2017 Task 1: Rich Features Based SVR for Semantic Textual Similarity Computing

2017-08-01 · SEMEVAL 2017 8 · Wenjie Liu, Chengjie Sun, Lei Lin, Bingquan Liu

Semantic Textual Similarity (STS) devotes to measuring the degree of equivalence in the underlying semantic of the sentence pair. We proposed a new system, ITNLP-AiKF, which applies in the SemEval 2017 Task1 Semantic Tex…

Feature Engineering regression Semantic Textual Similarity Sentence+1

STS-UHH at SemEval-2017 Task 1: Scoring Semantic Textual Similarity Using Supervised and Unsupervised Ensemble

2017-08-01 · SEMEVAL 2017 8 · Sarah Kohail, Amr Rekaby Salama, Chris Biemann

This paper reports the STS-UHH participation in the SemEval 2017 shared Task 1 of Semantic Textual Similarity (STS). Overall, we submitted 3 runs covering monolingual and cross-lingual STS tracks. Our participation invol…